Pratama, E. and Ismail, M.S. and Ridha, S. (2018) Development of a predictive model for enhanced gas recovery by CO2 huff-n-puff in depleted carbonate gas reservoirs. In: UNSPECIFIED.
Full text not available from this repository.Abstract
Injecting CO2 with huff-n-puff process is becoming an efficient technique to overcome some productivity damage and enhanced gas recovery in depleted gas reservoirs. Several numerical simulations are required to estimate the gas recovery factor obtained from CO2 huff-n-puff injection. However, numerical simulations are very expensive and time-consuming processes. This study aims to develop a predictive model to estimate the additional gas recovery factor by CO2 huff-n-puff injection in depleted carbonate gas reservoirs. To create the predictive model, a base case reservoir model was constructed based on a real carbonate gas field data. Subsequently, ranges of reservoir and CO2 huff-n-puff operation variables that affect the gas recovery factor were determined from published literature data. To obtain optimal spacing and cover all of the variable space, space filling design together with Latin hypercube method was then employed to construct 100 simulation cases prepared using CMG-GEM. Using multiple regression method, a linear predictive model was developed to estimate the additional gas recovery factor obtained from CO2 huff-n-puff injection in depleted carbonate gas reservoirs. The novelty of this model is in the ability to quick estimation of the additional gas recovery factor by CO2 huff-n-puff process using typical reservoir and huff-n-puff operation parameters. © 2018 Society of Petroleum Engineers. All rights reserved.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 0; Conference of 80th EAGE Conference and Exhibition 2018: Opportunities Presented by the Energy Transition ; Conference Date: 11 June 2018 Through 14 June 2018; Conference Code:148615 |
Uncontrolled Keywords: | Carbon dioxide; Carbonation; Gas industry; Numerical models; Petroleum reservoirs; Recovery; Regression analysis, Depleted gas reservoir; Enhanced gas recoveries; Linear predictive models; Multiple regression methods; Operation parameters; Operation variables; Predictive modeling; Space filling designs, Gases |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 16:37 |
Last Modified: | 09 Nov 2023 16:37 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/10637 |